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Record W4237780208 · doi:10.5296/ijim.v4i1.14470

Perceptions and Plans of Canadian Food and Beverage Businesses Regarding Cannabis as a Food Ingredient

2019· article· en· W4237780208 on OpenAlexaffabout
Sylvain Charlebois, Brian Sterling, Paul Medeiros

Bibliographic record

VenueInternational Journal of Industrial Marketing · 2019
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCannabisLegalizationBusinessIngredientProduct (mathematics)MarketingLegislationConsumablesMedicineLawPolitical science

Abstract

fetched live from OpenAlex

Cannabis-infused consumables may become a fact of life in Canada by the end of 2019 and, according to this study, food companies are already seriously considering their options for entering the cannabis-infused consumables market. Food and beverage businesses continuously search for growth; new products using cannabis as an ingredient are seen by many as a fresh market that is going to open significant opportunities for growth and earnings.This study does not look at the functional effects of cannabis, but rather food processors’ perceptions and plans regarding cannabis as a food ingredient once it is legalized. It explores several dimensions, including perceived risks associated with this embryonic sector, what those risks specifically might be, and any sense of competitive urgency that they may feel. Combined with a similar examination of Canadian consumer attitudes to cannabis consumables, published in January 2018 (Charlebois, Simogyi, & Sterling, 2018), the two reports provide a unique view of the potential opportunities, hazards, and impediments in this new market sector.A total of 294 food and beverage firms were surveyed in August 2018. Just under 40% of these organizations say they support legalization of cannabis-infused products, while a substantial minority (41%) are ambivalent. Over 65% of responding companies are concerned about the risks edibles represent to children and young adults. That said, 16.4% of surveyed companies confirmed that they are either planning to launch a product as soon as edibles are legal, or are already serving a market with such a product. The most commonly stated reason for not entering the cannabis consumables market is that cannabis is not compatible with their current product line. A general lack of understanding of cannabinoids was the second most popular reason given.The results highlight how just risk-adverse Canadian food industry leaders currently are regarding cannabis. Liability risks (47.1%) and reputational risks (20.1%) are cited as significant deterrents to entering the cannabis-infused consumables market. Other hazards include the lack of regulatory clarity, training of front-line staff, the residual social stigma of cannabis itself, questions about supply chain reliability, and the need for different, tamper-proof packaging.Plainly, regulatory questions remain top-of-mind for most company officials. Food and beverage firms say they are awaiting regulatory guidance as a condition of their plans. Respondents also state that governments are likely the key resource that they would employ during product and strategy development. More than 30% of respondents say governments are their primary choice, followed by their own internal resources. And 45.5% see government bearing the chief responsibility for addressing cannabis-infused edibles issues.At the time of this writing, Health Canada has said it expects to begin industry consultations concerning cannabis consumables early in 2019. Until then, based on this survey’s results, we perhaps should expect enthusiastic, yet limited, interest related to these products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.277
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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